Radiomics machine-learning signature for diagnosis of hepatocellular carcinoma in cirrhotic patients with indeterminate liver nodules.

Journal: European radiology
Published Date:

Abstract

PURPOSE: To enhance clinician's decision-making by diagnosing hepatocellular carcinoma (HCC) in cirrhotic patients with indeterminate liver nodules using quantitative imaging features extracted from triphasic CT scans.

Authors

  • Fatima-Zohra Mokrane
    Radiology Department, Rangueil University Hospital, Toulouse, France. mokrane_fatimazohra@yahoo.fr.
  • Lin Lu
    School of Economics and Management, Guangxi Normal University, Guilin, China.
  • Adrien Vavasseur
    Radiology Department, Rangueil University Hospital, Toulouse, France.
  • Philippe Otal
    Radiology Department, Rangueil University Hospital, Toulouse, France.
  • Jean-Marie Peron
    Hepatology Department, Purpan University Hospital, Toulouse, France.
  • Lyndon Luk
    Department of Radiology, New York Presbyterian Hospital, Columbia University Vagelos College of Physicians and Surgeons, New York City, NY, USA.
  • Hao Yang
    College of Agricultural Science and Engineering, Hohai University, Nanjing 210098, China.
  • Samy Ammari
    Service de Radiologie, Gustave-Roussy, Université Paris-Saclay, Villejuif, France.
  • Yvonne Saenger
    Department of Medicine, Division of Hematology/Oncology, Columbia University Medical Center/New York Presbyterian, New York, NY, USA.
  • Herve Rousseau
    Radiology Department, Rangueil University Hospital, Toulouse, France.
  • Binsheng Zhao
    Department of Radiology, Columbia University Medical Center, 630 West 168th Street, New York, NY 10032.
  • Lawrence H Schwartz
    Department of Radiology, Columbia University College of Physicians and Surgeons, New York, NY, USA.
  • Laurent Dercle
    Department of Radiology, Columbia University Medical Center, 630 West 168th Street, New York, NY 10032; Gustave Roussy, Université Paris-Saclay, Université Paris-Saclay, Département D'imagerie Médicale, Villejuif, France.